Jagannath International Management School
Within five years the prime driver of marketing success will be Personalization. Interacting with your customers and audiences taking into consideration their likes, preferences and interests, in a way that feels personal and human is Personalization in Marketing.
Nowadays what customers really want, tailored to their interests and needs is a personalized experience. Marketers also realized the value of personalization as survey has shown that 96% said that it helped them build better customer relationships, 61% found that personalization helped them deliver better customer experience which is the key brand differentiator for customers, more so than price and product and 88% felt that they perceived a jump in business results. Today predominantly by deploying triggered communications and product recommendations within singular channels, personalization leaders have found 10 to 30 percent increases in marketing-spend efficiency and almost drive 5 to 15 percent increases in revenue.Hence to build the best personalized campaigns our customer data is the most valuable thing to leverage upon and for which automation and data analytics have come into picture.
Personalization is the next wave of the communal public user experience. Hence to stay ahead of the curve the capabilities companies need to develop are advances in technology, data and analytics which will allow marketers to create ‘human’ and personal experiences across channels, moments and buying stages.
Three major shifts in personalization over the next five years will be:
‘Digitized’ Physical spaces
The next horizon for personalization as per survey data will be “offline” person-to-person experiences. 44 percent of CMOs say to provide a personalized offering frontline employees will rely on insights from advanced analytics; 37 percent say that location, facial recognition, and biometric sensors will become more widely used, 40 percent say AI-enabled tools to improve service will be used by personal shoppers.
Scale Empathy
Machine learning is getting much better at reacting andreading to emotional cues. Understanding social cues and adapting to them is how people build trust. More sophisticated algorithms aremore effectively allowing programs to interpret new kinds of data (visual, auditory) and extrapolate emotions than in the past.
To personalize journeys end-to-endBrands will use ecosystems
Brands provide more consistent and seamless consumer experiences across all stages of their decision journeys with the help of expanding partner ecosystems. Industries as diverse as healthcare, retail and banking are improving customer service and expanding the array and quality of solutions offered by forging ecosystems comprising a variety of businesses from different sectors .
Turning the future into reality:
Customer data and analytics foundations Investment: Top marketers are developing algorithms to identify customer propensity and behavioral patterns, analytical capabilities to feed the information into easy-to use dashboards and systems that can pool and analyze structured and unstructured data.To build and refresh the organization’s martech road map,track pilot performance, develop use cases, and compile a robust library oflessons learned and standards, a product-management teamshould be established with representation from both IT and marketing. CDPs (customer-data platform) provide built-in machine-learning automation that can cleanse external and internal data, cookies, and ad networks, connect a single customer across devices, and enable real-time campaign execution across channels and touch points.
Recruit and train translators and advanced tech talent:
Analytics translators will be needed by marketing organization to communicate business goals to tech stakeholders and data-driven outcomes to the business. For developing cutting-edge personalization capabilities, recruiting and developing translator talent will provide a significant competitive advantage.
Building agile capabilities:
For personalization, commitment to agile management is required. Cross-functional teams and performance measurement must evolve similarly and become more focused on testing velocity, success rates, and creative boldness. To assess current initiatives and chart new ones, realign funding and resources in support of key priorities, strategy processes & annual budgeting should be flexible with frequent reviews.Collaborating and solving problems with colleagues from across the organization, in IT, product development,analytics and legal is equally important.
Protect Customer privacy protection:
Companies should proactively manage customer privacy at the cutting edge of personalization innovation .Privacy policy considerations and Data governance considerations must become a part of a marketing organization’s standard operating model. Personalization is becoming more pervasive.Companies can hopeto deliver value to both their customers and brandsonly by acting today.Thanks to developments like artificial intelligence (AI), cloud solutions, machine learning, marketing strategies and approaches, data analytics have evolved drastically in only a few years
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